Due to the Web expansion, the prediction of online news popularity is becoming a trendy
research topic. In this paper, we propose a novel and proactive Intelligent Decision Support …

News articles are an engaging type of online content that captures the attention of a
significant amount of Internet users. They are particularly enjoyed by mobile users and …

Understanding user participation is fundamental in anticipating the popularity of online
content. In this paper, we explore how the number of users' comments during a short …

News articles are extremely time sensitive by nature. There is also intense competition
among news items to propagate as widely as possible. Hence, the task of predicting the …

Consuming news articles is an integral part of our daily lives and news agencies such as
The Washington Post (WP) expend tremendous effort in providing high quality reading …

As social networks become a major source of information, predicting the outcome of
information diffusion has appeared intriguing to both researchers and practitioners. By …

Social media platforms have democratized the process of web content creation allowing
mere consumers to become creators and distributors of content. But this has also contributed …

In the current Web 2.0 era, the popularity of Web resources fluctuates ephemerally, based
on trends and social interest. As a result, content-based relevance signals are insufficient to …

Online news is a media for people to get new information. There are a lot of online news
media out there and a many people will only read news that is interesting for them. This kind …

Predicting the popularity of online article sheds light to many applications such as
recommendation, advertising and information retrieval. However, there are several technical …